Risk factors and model construction of severe multiple injuries complicated with AKI
Objective To explore the prediction model of acute kidney injury(AKI)in patients with severe multiple injuries in intensive care unit(ICU)based on hemodynamic indexes,clinical characteristics and laboratory indexes.Methods 98 patients with severe multiple injuries in ICU admitted to our hospital from January 2018 to October 2023 were selected as the research object.According to whether the patients were compli-cated with AKI within 72 hours after admission,they were divided into two groups:the complicated AKI group(31 cases)and the non-complicated A-KI group(67 cases),and their clinical data were collected retrospectively.The hemodynamic indexes,clinical characteristics and laboratory indexes of the two groups were compared.Logistic regression was used to explore the risk factors of patients with severe multiple injuries complicated with AKI in ICU,and the predictive value of the model was evaluated by receiver operating characteristic(ROC)curve.Results Stepwise multivariate Logis-tic analysis showed that the independent risk factors of AKI in ICU patients with severe multiple injuries were high levels of serum lactic acid and PCT(OR=2.344,2.442,P＜0.05),and high eRPP was the protective factor(OR=0.480,P＜0.05).According to the Logistic regression results of severe multiple trauma patients complicated with AKI in ICU,ROC curve was used to evaluate the predictive value of the model.The results showed that the AUC value of the predictive model for severe multiple trauma patients complicated with AKI in ICU was 0.863,the diagnostic sensitivity of the model was 80.65%,and the specificity was 73.13%,suggesting that the model had good discrimination.Hosmer-Lemeshow goodness-of-fit test shows that the model had a good fitting effect,Chi-Square=6.486,DF=6,P=0.653.Conclusion The risk factors of AKI in ICU patients with severe multiple injuries include high levels of serum lactic acid and PCT,and high eRPP is the protective factor.The construction of prediction model can provide ba-sis for the formulation of preventive measures and ultimately improve the prognosis of patients.
Intensive care unitMultiple injuriesAcute kidney injuryHemodynamicsClinical features
NETL
NSTL
万方数据
维普
